{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:17:24.970283Z",
     "end_time": "2023-05-18T12:17:24.980278Z"
    }
   },
   "outputs": [],
   "source": [
    "import pywt\n",
    "import mne\n",
    "import numpy as np\n",
    "WAVELETNAME = 'morl'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "from MyEDFImports import import_ecg, get_edf_filenames\n",
    "names = get_edf_filenames()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:17:24.975278Z",
     "end_time": "2023-05-18T12:17:24.991277Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting EDF parameters from /mnt/c/Tadeusz/mgr_sleep_states/Jean-Pol_repaired_headers/CN223100.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "NOTE: pick_channels() is a legacy function. New code should use inst.pick(...).\n"
     ]
    },
    {
     "data": {
      "text/plain": "array([[-8.79697871e-05, -8.69626917e-05, -8.49485008e-05, ...,\n        -2.07209888e-04, -2.27150378e-04, -2.36415656e-04]])"
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw = import_ecg(names[0])\n",
    "raw.crop(100,120)\n",
    "raw[0][0]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T13:48:17.796897Z",
     "end_time": "2023-05-18T13:48:18.002261Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "outputs": [
    {
     "data": {
      "text/plain": "array([0.002, 0.002, 0.002, ..., 0.002, 0.002, 0.002])"
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time = raw[0][1]\n",
    "values = raw[0][0].reshape(-1)\n",
    "d_time = np.diff(time)\n",
    "d_time"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T13:00:18.303300Z",
     "end_time": "2023-05-18T13:00:19.655268Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 15611000)\n",
      "(15611000,)\n",
      "(15611000,)\n"
     ]
    }
   ],
   "source": [
    "print(raw[0][0].shape)\n",
    "print(raw[0][1].shape)\n",
    "print(values.shape)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T13:00:21.730304Z",
     "end_time": "2023-05-18T13:00:22.997737Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "outputs": [
    {
     "data": {
      "text/plain": "False"
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_val = np.diff(values)\n",
    "d_val[::2]\n",
    "all_zeros = not np.any(d_val)\n",
    "all_zeros"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T13:38:02.370506Z",
     "end_time": "2023-05-18T13:38:02.435545Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "sin = [np.sin(t) for t in np.linspace(0,40,num=100)]\n",
    "plt.plot(sin)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "outputs": [
    {
     "data": {
      "text/plain": "(15611000, 0)"
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values\n",
    "d_val = np.diff(values)\n",
    "d_val.shape"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:56:18.071000Z",
     "end_time": "2023-05-18T12:56:18.076005Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "sin = [np.sin(t) for t in np.linspace(0,40,num=100)]\n",
    "plt.plot(sin)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x7feef2c0cd30>]"
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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66zZixAi7evWq07dkyRKbMGGC833Dhg0WDAZ7nfN21/LHYrGYSbJYLNbnbQAAwN3V1+u3pztPPT09am1tVXFxsdOXnp6u4uJiNTc3p9ymubnZVS9JJSUlTv3p06cVjUZdNcFgUJFIpNc5JSkWi+n+++937efpp5+Wz+dz7efEiRP68MMPnb6PPvpIY8aMUW5ursrKynTkyBFn7HbXcvXqVcXjcVcDAAADk6fwdOnSJSUSCYVCIVd/KBRSNBpNuU00Gr1p/fVPL3OeOnVKq1ev1qJFi265n0/uY8KECXrjjTe0bds2/eIXv1AymdT06dN17ty5216LJNXU1CgYDDotNze311oAANC/9bu37c6fP6/S0lLNmTNHzz33nKdtCwoKtGDBAj322GMqLCzU1q1b9cADD2jdunWfak3Lli1TLBZz2tmzZz/VfAAA4IvLU3gaOXKkBg0apM7OTld/Z2enwuFwym3C4fBN669/9mXOCxcuaMaMGZo+ffoND4L3tp9P7uOPDRkyRI8//rhOnTrleS2f5Pf7lZmZ6WoAAGBg8hSefD6fpk6dqqamJqcvmUyqqalJBQUFKbcpKChw1UvSrl27nPq8vDyFw2FXTTweV0tLi2vO8+fP65lnntHUqVO1YcMGpae7l15QUKA333xT165dc+1nwoQJGjFiRMq1JRIJHT58WNnZ2Z7WAgAA7mFen0RvbGw0v99vGzdutKNHj9rChQstKyvLotGomZnNnz/fli5d6tS/9dZbNnjwYFu5cqUdO3bMqqurbciQIXb48GGnpra21rKysmzbtm126NAhKysrs7y8PLty5YqZmZ07d87GjRtnRUVFdu7cOevo6HDadV1dXRYKhWz+/PnW3t5ujY2NNnToUFu3bp1T84Mf/MB+9atf2b//+79ba2urfeMb37BAIGBHjhzp81r6grftAADof/p6/fYcnszMVq9ebaNHjzafz2f5+fm2b98+Z6ywsNAqKipc9Zs3b7bx48ebz+ezSZMm2Y4dO1zjyWTSli9fbqFQyPx+vxUVFdmJEyec8Q0bNpiklO2TDh48aE8++aT5/X4bNWqU1dbWusZffPFFZ92hUMhmzZplBw4c8LSWviA8AQDQ//T1+p1mZna37noNVPF4XMFgULFYjOefAADoJ/p6/e53b9sBAADcTYQnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4MFthac1a9Zo7NixCgQCikQi2r9//03rt2zZookTJyoQCGjy5MnauXOna9zMtGLFCmVnZysjI0PFxcU6efKkM/7uu++qsrJSeXl5ysjI0COPPKLq6mr19PS45jl06JCeeuopBQIB5ebmqq6uzjX+d3/3d3rqqac0YsQIjRgxQsXFxTes/Vvf+pbS0tJcrbS09HZOEwAAGIA8h6dNmzapqqpK1dXVOnDggKZMmaKSkhJdvHgxZf3evXs1b948VVZWqq2tTeXl5SovL1d7e7tTU1dXp1WrVmnt2rVqaWnRsGHDVFJSou7ubknS8ePHlUwmtW7dOh05ckSvvvqq1q5dq5deesmZIx6Pa+bMmRozZoxaW1tVX1+vl19+WevXr3dq9uzZo3nz5mn37t1qbm5Wbm6uZs6cqfPnz7vWXFpaqo6ODqc1NDR4PU0AAGCgMo/y8/Nt8eLFzvdEImE5OTlWU1OTsn7u3Lk2e/ZsV18kErFFixaZmVkymbRwOGz19fXOeFdXl/n9fmtoaOh1HXV1dZaXl+d8f/31123EiBF29epVp2/JkiU2YcKEXuf4+OOPbfjw4fb3f//3Tl9FRYWVlZX1uk1fxGIxk2SxWOxTzQMAAD4/fb1+e7rz1NPTo9bWVhUXFzt96enpKi4uVnNzc8ptmpubXfWSVFJS4tSfPn1a0WjUVRMMBhWJRHqdU5JisZjuv/9+136efvpp+Xw+135OnDihDz/8MOUcv//973Xt2jXXPNIf7lA9+OCDmjBhgl544QW9//77va5Dkq5evap4PO5qAABgYPIUni5duqREIqFQKOTqD4VCikajKbeJRqM3rb/+6WXOU6dOafXq1Vq0aNEt9/PJffyxJUuWKCcnxxXcSktL9fOf/1xNTU368Y9/rN/+9rf66le/qkQikXIOSaqpqVEwGHRabm5ur7UAAKB/G3y3F+DV+fPnVVpaqjlz5ui555677Xlqa2vV2NioPXv2KBAIOP3f+MY3nP89efJkffnLX9YjjzyiPXv2qKioKOVcy5YtU1VVlfM9Ho8ToAAAGKA83XkaOXKkBg0apM7OTld/Z2enwuFwym3C4fBN669/9mXOCxcuaMaMGZo+fbrrQfCb7eeT+7hu5cqVqq2t1b/8y7/oy1/+cq/HK0kPP/ywRo4cqVOnTvVa4/f7lZmZ6WoAAGBg8hSefD6fpk6dqqamJqcvmUyqqalJBQUFKbcpKChw1UvSrl27nPq8vDyFw2FXTTweV0tLi2vO8+fP65lnntHUqVO1YcMGpae7l15QUKA333xT165dc+1nwoQJGjFihNNXV1en//E//of++Z//WdOmTbvlMZ87d07vv/++srOzb1kLAADuAV6fRG9sbDS/328bN260o0eP2sKFCy0rK8ui0aiZmc2fP9+WLl3q1L/11ls2ePBgW7lypR07dsyqq6ttyJAhdvjwYaemtrbWsrKybNu2bXbo0CErKyuzvLw8u3LlipmZnTt3zsaNG2dFRUV27tw56+jocNp1XV1dFgqFbP78+dbe3m6NjY02dOhQW7dunWs/Pp/PfvnLX7rmuHz5spmZXb582b73ve9Zc3OznT592n7961/bE088YY8++qh1d3f3+Rzxth0AAP1PX6/fnsOTmdnq1att9OjR5vP5LD8/3/bt2+eMFRYWWkVFhat+8+bNNn78ePP5fDZp0iTbsWOHazyZTNry5cstFAqZ3++3oqIiO3HihDO+YcMGk5SyfdLBgwftySefNL/fb6NGjbLa2lrX+JgxY1LOUV1dbWZmv//9723mzJn2wAMP2JAhQ2zMmDH23HPPOcGwrwhPAAD0P329fqeZmd2FG14DWjweVzAYVCwW4/knAAD6ib5ev/nbdgAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHtxWe1qxZo7FjxyoQCCgSiWj//v03rd+yZYsmTpyoQCCgyZMna+fOna5xM9OKFSuUnZ2tjIwMFRcX6+TJk874u+++q8rKSuXl5SkjI0OPPPKIqqur1dPT45rn0KFDeuqppxQIBJSbm6u6urrPfC0AAODe5jk8bdq0SVVVVaqurtaBAwc0ZcoUlZSU6OLFiynr9+7dq3nz5qmyslJtbW0qLy9XeXm52tvbnZq6ujqtWrVKa9euVUtLi4YNG6aSkhJ1d3dLko4fP65kMql169bpyJEjevXVV7V27Vq99NJLzhzxeFwzZ87UmDFj1Nraqvr6er388stav379Z7oWAABwjzOP8vPzbfHixc73RCJhOTk5VlNTk7J+7ty5Nnv2bFdfJBKxRYsWmZlZMpm0cDhs9fX1znhXV5f5/X5raGjodR11dXWWl5fnfH/99ddtxIgRdvXqVadvyZIlNmHChDu+lj8Wi8VMksVisT5vAwAA7q6+Xr893Xnq6elRa2uriouLnb709HQVFxerubk55TbNzc2uekkqKSlx6k+fPq1oNOqqCQaDikQivc4pSbFYTPfff79rP08//bR8Pp9rPydOnNCHH354R9dy9epVxeNxVwMAAAOTp/B06dIlJRIJhUIhV38oFFI0Gk25TTQavWn99U8vc546dUqrV6/WokWLbrmfT+7jTqxFkmpqahQMBp2Wm5vbay0AAOjf+t3bdufPn1dpaanmzJmj55577m4vR5K0bNkyxWIxp509e/ZuLwkAANwhnsLTyJEjNWjQIHV2drr6Ozs7FQ6HU24TDodvWn/9sy9zXrhwQTNmzND06dNdD4LfbD+f3MdnuZZP8vv9yszMdDUAADAweQpPPp9PU6dOVVNTk9OXTCbV1NSkgoKClNsUFBS46iVp165dTn1eXp7C4bCrJh6Pq6WlxTXn+fPn9cwzz2jq1KnasGGD0tPdSy8oKNCbb76pa9euufYzYcIEjRgx4jNdCwAAuId5fRK9sbHR/H6/bdy40Y4ePWoLFy60rKwsi0ajZmY2f/58W7p0qVP/1ltv2eDBg23lypV27Ngxq66utiFDhtjhw4edmtraWsvKyrJt27bZoUOHrKyszPLy8uzKlStmZnbu3DkbN26cFRUV2blz56yjo8Np13V1dVkoFLL58+dbe3u7NTY22tChQ23dunWf6Vr6grftAADof/p6/fYcnszMVq9ebaNHjzafz2f5+fm2b98+Z6ywsNAqKipc9Zs3b7bx48ebz+ezSZMm2Y4dO1zjyWTSli9fbqFQyPx+vxUVFdmJEyec8Q0bNpiklO2TDh48aE8++aT5/X4bNWqU1dbW3rD2T7uWviA8AQDQ//T1+p1mZna37noNVPF4XMFgULFYjOefAADoJ/p6/e53b9sBAADcTYQnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4MFthac1a9Zo7NixCgQCikQi2r9//03rt2zZookTJyoQCGjy5MnauXOna9zMtGLFCmVnZysjI0PFxcU6efKkq+ZHP/qRpk+frqFDhyorKyvlfpqamjR9+nQNHz5c4XBYS5Ys0ccff+yMv/zyy0pLS7uhDRs2zKnZuHHjDeOBQMDjGQIAAAOV5/C0adMmVVVVqbq6WgcOHNCUKVNUUlKiixcvpqzfu3ev5s2bp8rKSrW1tam8vFzl5eVqb293aurq6rRq1SqtXbtWLS0tGjZsmEpKStTd3e3U9PT0aM6cOXrhhRdS7ufgwYOaNWuWSktL1dbWpk2bNmn79u1aunSpU/O9731PHR0drvaf//N/1pw5c1xzZWZmumree+89r6cJAAAMVOZRfn6+LV682PmeSCQsJyfHampqUtbPnTvXZs+e7eqLRCK2aNEiMzNLJpMWDoetvr7eGe/q6jK/328NDQ03zLdhwwYLBoM39C9btsymTZvm6tu+fbsFAgGLx+Mp1/bOO++YJHvzzTdvOb8XsVjMJFksFvtU8wAAgM9PX6/fnu489fT0qLW1VcXFxU5fenq6iouL1dzcnHKb5uZmV70klZSUOPWnT59WNBp11QSDQUUikV7nTOXq1as3/HotIyND3d3dam1tTbnNT3/6U40fP15PPfWUq/+jjz7SmDFjlJubq7KyMh05cuSW+47H464GAAAGJk/h6dKlS0okEgqFQq7+UCikaDSacptoNHrT+uufXuZMpaSkRHv37lVDQ4MSiYTOnz+vV155RZLU0dFxQ313d7f+4R/+QZWVla7+CRMm6I033tC2bdv0i1/8QslkUtOnT9e5c+d63XdNTY2CwaDTcnNz+7xuAADQvwyYt+1mzpyp+vp6Pf/88/L7/Ro/frxmzZol6Q93x/7YP/7jP+ry5cuqqKhw9RcUFGjBggV67LHHVFhYqK1bt+qBBx7QunXret33smXLFIvFnHb27NnP9uAAAMAXhqfwNHLkSA0aNEidnZ2u/s7OToXD4ZTbhMPhm9Zf//QyZ2+qqqrU1dWlM2fO6NKlSyorK5MkPfzwwzfU/vSnP9XXvva1G+54/bEhQ4bo8ccf16lTp3qt8fv9yszMdDUAADAweQpPPp9PU6dOVVNTk9OXTCbV1NSkgoKClNsUFBS46iVp165dTn1eXp7C4bCrJh6Pq6Wlpdc5byYtLU05OTnKyMhQQ0ODcnNz9cQTT7hqTp8+rd27d9/wK7tUEomEDh8+rOzsbM9rAQAAA89grxtUVVWpoqJC06ZNU35+vl577TX97ne/07PPPitJWrBggUaNGqWamhpJ0ne/+10VFhbqJz/5iWbPnq3Gxka9/fbbWr9+vaQ/hJ0XX3xRP/zhD/Xoo48qLy9Py5cvV05OjsrLy539njlzRh988IHOnDmjRCKhd955R5I0btw43XfffZKk+vp6lZaWKj09XVu3blVtba02b96sQYMGuY7hjTfeUHZ2tr761a/ecHyvvPKKvvKVr2jcuHHq6upSfX293nvvPX3729/2eqoAAMBAdDuv8q1evdpGjx5tPp/P8vPzbd++fc5YYWGhVVRUuOo3b95s48ePN5/PZ5MmTbIdO3a4xpPJpC1fvtxCoZD5/X4rKiqyEydOuGoqKipM0g1t9+7dTs2MGTMsGAxaIBCwSCRiO3fuvGHtiUTCHnroIXvppZdSHtuLL77oHFsoFLJZs2bZgQMHPJ0f/qkCAAD6n75ev9PMzO5idhuQ4vG4gsGgYrEYzz8BANBP9PX6PWDetgMAAPg8EJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB7cVntasWaOxY8cqEAgoEolo//79N63fsmWLJk6cqEAgoMmTJ2vnzp2ucTPTihUrlJ2drYyMDBUXF+vkyZOumh/96EeaPn26hg4dqqysrJT7aWpq0vTp0zV8+HCFw2EtWbJEH3/8sTP+7rvvKi0t7Ya2b98+T+sFAAD3Ls/hadOmTaqqqlJ1dbUOHDigKVOmqKSkRBcvXkxZv3fvXs2bN0+VlZVqa2tTeXm5ysvL1d7e7tTU1dVp1apVWrt2rVpaWjRs2DCVlJSou7vbqenp6dGcOXP0wgsvpNzPwYMHNWvWLJWWlqqtrU2bNm3S9u3btXTp0htqf/3rX6ujo8NpU6dO9bReAABwDzOP8vPzbfHixc73RCJhOTk5VlNTk7J+7ty5Nnv2bFdfJBKxRYsWmZlZMpm0cDhs9fX1znhXV5f5/X5raGi4Yb4NGzZYMBi8oX/ZsmU2bdo0V9/27dstEAhYPB43M7PTp0+bJGtra+v1+G613r6IxWImyWKxWJ+3AQAAd1dfr9+e7jz19PSotbVVxcXFTl96erqKi4vV3Nyccpvm5mZXvSSVlJQ49adPn1Y0GnXVBINBRSKRXudM5erVqwoEAq6+jIwMdXd3q7W11dX/9a9/XQ8++KCefPJJbd++3dN6e9t3PB53NQAAMDB5Ck+XLl1SIpFQKBRy9YdCIUWj0ZTbRKPRm9Zf//QyZyolJSXau3evGhoalEgkdP78eb3yyiuSpI6ODknSfffdp5/85CfasmWLduzYoSeffFLl5eWuAHWr9aZSU1OjYDDotNzc3D6vGwAA9C8D5m27mTNnqr6+Xs8//7z8fr/Gjx+vWbNmSfrD3TFJGjlypKqqqhSJRPRf/st/UW1trb75zW+qvr7+U+172bJlisViTjt79uynPh4AAPDF5Ck8jRw5UoMGDVJnZ6erv7OzU+FwOOU24XD4pvXXP73M2Zuqqip1dXXpzJkzunTpksrKyiRJDz/8cK/bRCIRnTp1qs/rTcXv9yszM9PVAADAwOQpPPl8Pk2dOlVNTU1OXzKZVFNTkwoKClJuU1BQ4KqXpF27djn1eXl5CofDrpp4PK6WlpZe57yZtLQ05eTkKCMjQw0NDcrNzdUTTzzRa/0777yj7OzsPq8XAADc2wZ73aCqqkoVFRWaNm2a8vPz9dprr+l3v/udnn32WUnSggULNGrUKNXU1EiSvvvd76qwsFA/+clPNHv2bDU2Nurtt9/W+vXrJf0h7Lz44ov64Q9/qEcffVR5eXlavny5cnJyVF5e7uz3zJkz+uCDD3TmzBklEgm98847kqRx48bpvvvukyTV19ertLRU6enp2rp1q2pra7V582YNGjRIkvT3f//38vl8evzxxyVJW7du1RtvvKGf/vSnzn5utV4AAHCPu51X+VavXm2jR482n89n+fn5tm/fPmessLDQKioqXPWbN2+28ePHm8/ns0mTJtmOHTtc48lk0pYvX26hUMj8fr8VFRXZiRMnXDUVFRUm6Ya2e/dup2bGjBkWDAYtEAhYJBKxnTt3uubYuHGjfelLX7KhQ4daZmam5efn25YtW244vlut91b4pwoAAOh/+nr9TjMzu4vZbUCKx+MKBoOKxWI8/wQAQD/R1+v3gHnbDgAA4PNAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAe3FZ4WrNmjcaOHatAIKBIJKL9+/fftH7Lli2aOHGiAoGAJk+erJ07d7rGzUwrVqxQdna2MjIyVFxcrJMnT7pqfvSjH2n69OkaOnSosrKyUu6nqalJ06dP1/DhwxUOh7VkyRJ9/PHHzviePXtUVlam7OxsDRs2TI899pj+4R/+wTXHxo0blZaW5mqBQMDD2QEAAAOZ5/C0adMmVVVVqbq6WgcOHNCUKVNUUlKiixcvpqzfu3ev5s2bp8rKSrW1tam8vFzl5eVqb293aurq6rRq1SqtXbtWLS0tGjZsmEpKStTd3e3U9PT0aM6cOXrhhRdS7ufgwYOaNWuWSktL1dbWpk2bNmn79u1aunSpay1f/vKX9b/+1//SoUOH9Oyzz2rBggX6P//n/7jmyszMVEdHh9Pee+89r6cJAAAMVOZRfn6+LV682PmeSCQsJyfHampqUtbPnTvXZs+e7eqLRCK2aNEiMzNLJpMWDoetvr7eGe/q6jK/328NDQ03zLdhwwYLBoM39C9btsymTZvm6tu+fbsFAgGLx+O9Hs+sWbPs2WefveX8XsRiMZNksVjsU80DAAA+P329fnu689TT06PW1lYVFxc7fenp6SouLlZzc3PKbZqbm131klRSUuLUnz59WtFo1FUTDAYViUR6nTOVq1ev3vDrtYyMDHV3d6u1tbXX7WKxmO6//35X30cffaQxY8YoNzdXZWVlOnLkyC33HY/HXQ0AAAxMnsLTpUuXlEgkFAqFXP2hUEjRaDTlNtFo9Kb11z+9zJlKSUmJ9u7dq4aGBiUSCZ0/f16vvPKKJKmjoyPlNps3b9a//du/6dlnn3X6JkyYoDfeeEPbtm3TL37xCyWTSU2fPl3nzp3rdd81NTUKBoNOy83N7fO6AQBA/zJg3rabOXOm6uvr9fzzz8vv92v8+PGaNWuWpD/cHftju3fv1rPPPqu/+7u/06RJk5z+goICLViwQI899pgKCwu1detWPfDAA1q3bl2v+162bJlisZjTzp49+9kfIAAA+ELwFJ5GjhypQYMGqbOz09Xf2dmpcDiccptwOHzT+uufXubsTVVVlbq6unTmzBldunRJZWVlkqSHH37YVffb3/5Wf/Inf6JXX31VCxYsuOmcQ4YM0eOPP65Tp071WuP3+5WZmelqAABgYPIUnnw+n6ZOnaqmpianL5lMqqmpSQUFBSm3KSgocNVL0q5du5z6vLw8hcNhV008HldLS0uvc95MWlqacnJylJGRoYaGBuXm5uqJJ55wxvfs2aPZs2frxz/+sRYuXHjL+RKJhA4fPqzs7GzPawEAAAPPYK8bVFVVqaKiQtOmTVN+fr5ee+01/e53v3OeG1qwYIFGjRqlmpoaSdJ3v/tdFRYW6ic/+Ylmz56txsZGvf3221q/fr2kP4SdF198UT/84Q/16KOPKi8vT8uXL1dOTo7Ky8ud/Z45c0YffPCBzpw5o0QioXfeeUeSNG7cON13332SpPr6epWWlio9PV1bt25VbW2tNm/erEGDBkn6w6/qvva1r+m73/2u/vRP/9R5psrn8zkPjb/yyiv6yle+onHjxqmrq0v19fV677339O1vf/s2Ti8AABhwbudVvtWrV9vo0aPN5/NZfn6+7du3zxkrLCy0iooKV/3mzZtt/Pjx5vP5bNKkSbZjxw7XeDKZtOXLl1soFDK/329FRUV24sQJV01FRYVJuqHt3r3bqZkxY4YFg0ELBAIWiURs586dfZqjsLDQqXnxxRedYwuFQjZr1iw7cOCAp/PDP1UAAED/09frd5qZ2d2JbQNXPB5XMBhULBbj+ScAAPqJvl6/B8zbdgAAAJ8HwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAADwhPAAAAHhCeAAAAPCA8AQAAeEB4AgAA8IDwBAAA4AHhCQAAwAPCEwAAgAeEJwAAAA8ITwAAAB4QngAAADwgPAEAAHhAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADw4LbC05o1azR27FgFAgFFIhHt37//pvVbtmzRxIkTFQgENHnyZO3cudM1bmZasWKFsrOzlZGRoeLiYp08edJV86Mf/UjTp0/X0KFDlZWVlXI/TU1Nmj59uoYPH65wOKwlS5bo448/dtUcOnRITz31lAKBgHJzc1VXV+d5vQAA4N7lOTxt2rRJVVVVqq6u1oEDBzRlyhSVlJTo4sWLKev37t2refPmqbKyUm1tbSovL1d5ebna29udmrq6Oq1atUpr165VS0uLhg0bppKSEnV3dzs1PT09mjNnjl544YWU+zl48KBmzZql0tJStbW1adOmTdq+fbuWLl3q1MTjcc2cOVNjxoxRa2ur6uvr9fLLL2v9+vWe1gsAAO5h5lF+fr4tXrzY+Z5IJCwnJ8dqampS1s+dO9dmz57t6otEIrZo0SIzM0smkxYOh62+vt4Z7+rqMr/fbw0NDTfMt2HDBgsGgzf0L1u2zKZNm+bq2759uwUCAYvH42Zm9vrrr9uIESPs6tWrTs2SJUtswoQJfV5vX8RiMZNksVisz9sAAIC7q6/Xb093nnp6etTa2qri4mKnLz09XcXFxWpubk65TXNzs6tekkpKSpz606dPKxqNumqCwaAikUivc6Zy9epVBQIBV19GRoa6u7vV2trqrOXpp5+Wz+dzreXEiRP68MMP+7Te3vYdj8ddDQAADEyewtOlS5eUSCQUCoVc/aFQSNFoNOU20Wj0pvXXP73MmUpJSYn27t2rhoYGJRIJnT9/Xq+88ookqaOj46Zr+eQ6brXeVGpqahQMBp2Wm5vb53UDAID+ZcC8bTdz5kzV19fr+eefl9/v1/jx4zVr1ixJf7g7dictW7ZMsVjMaWfPnr2j+wMAAHePp1QxcuRIDRo0SJ2dna7+zs5OhcPhlNuEw+Gb1l//9DJnb6qqqtTV1aUzZ87o0qVLKisrkyQ9/PDDN13LJ9dxq/Wm4vf7lZmZ6WoAAGBg8hSefD6fpk6dqqamJqcvmUyqqalJBQUFKbcpKChw1UvSrl27nPq8vDyFw2FXTTweV0tLS69z3kxaWppycnKUkZGhhoYG5ebm6oknnnDW8uabb+ratWuutUyYMEEjRozo03oBAMA9zuuT6I2Njeb3+23jxo129OhRW7hwoWVlZVk0GjUzs/nz59vSpUud+rfeessGDx5sK1eutGPHjll1dbUNGTLEDh8+7NTU1tZaVlaWbdu2zQ4dOmRlZWWWl5dnV65ccWree+89a2trsx/84Ad23333WVtbm7W1tdnly5edmrq6Ojt06JC1t7fbK6+8YkOGDLF//Md/dMa7urosFArZ/Pnzrb293RobG23o0KG2bt06T+u9Fd62AwCg/+nr9dtzeDIzW716tY0ePdp8Pp/l5+fbvn37nLHCwkKrqKhw1W/evNnGjx9vPp/PJk2aZDt27HCNJ5NJW758uYVCIfP7/VZUVGQnTpxw1VRUVJikG9ru3budmhkzZlgwGLRAIGCRSMR27tx5w9oPHjxoTz75pPn9fhs1apTV1tbeUHOr9d4K4QkAgP6nr9fvNDOzu3bba4CKx+MKBoOKxWI8/wQAQD/R1+v3gHnbDgAA4PNAeAIAAPCA8AQAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4MPhuL2Aguv6Ptsfj8bu8EgAA0FfXr9u3+uMrhKc74PLly5Kk3Nzcu7wSAADg1eXLlxUMBnsd52/b3QHJZFIXLlzQ8OHDlZaWdreXc1fF43Hl5ubq7Nmz/J2/O4jz/PnhXH8+OM+fD86zm5np8uXLysnJUXp67082cefpDkhPT9dDDz10t5fxhZKZmcn/MT8HnOfPD+f688F5/nxwnv9/N7vjdB0PjAMAAHhAeAIAAPCA8IQ7yu/3q7q6Wn6//24vZUDjPH9+ONefD87z54PzfHt4YBwAAMAD7jwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITPrUPPvhAf/7nf67MzExlZWWpsrJSH3300U236e7u1uLFi/Wf/tN/0n333ac//dM/VWdnZ8ra999/Xw899JDS0tLU1dV1B46gf7gT5/ngwYOaN2+ecnNzlZGRoS996Uv6m7/5mzt9KF8oa9as0dixYxUIBBSJRLR///6b1m/ZskUTJ05UIBDQ5MmTtXPnTte4mWnFihXKzs5WRkaGiouLdfLkyTt5CP3CZ3mer127piVLlmjy5MkaNmyYcnJytGDBAl24cOFOH0a/8Fn/TH/S888/r7S0NL322muf8ar7GQM+pdLSUpsyZYrt27fP/vVf/9XGjRtn8+bNu+k2zz//vOXm5lpTU5O9/fbb9pWvfMWmT5+esrasrMy++tWvmiT78MMP78AR9A934jz/7Gc/s+985zu2Z88e+/d//3f7n//zf1pGRoatXr36Th/OF0JjY6P5fD5744037MiRI/bcc89ZVlaWdXZ2pqx/6623bNCgQVZXV2dHjx61v/7rv7YhQ4bY4cOHnZra2loLBoP2v//3/7aDBw/a17/+dcvLy7MrV658Xof1hfNZn+euri4rLi62TZs22fHjx625udny8/Nt6tSpn+dhfSHdiZ/p67Zu3WpTpkyxnJwce/XVV+/wkXyxEZ7wqRw9etQk2b/92785ff/0T/9kaWlpdv78+ZTbdHV12ZAhQ2zLli1O37Fjx0ySNTc3u2pff/11KywstKampns6PN3p8/xJf/EXf2EzZsz47Bb/BZafn2+LFy92vicSCcvJybGampqU9XPnzrXZs2e7+iKRiC1atMjMzJLJpIXDYauvr3fGu7q6zO/3W0NDwx04gv7hsz7Pqezfv98k2XvvvffZLLqfulPn+ty5czZq1Chrb2+3MWPG3PPhiV/b4VNpbm5WVlaWpk2b5vQVFxcrPT1dLS0tKbdpbW3VtWvXVFxc7PRNnDhRo0ePVnNzs9N39OhRvfLKK/r5z39+0z/QeC+4k+f5j8ViMd1///2f3eK/oHp6etTa2uo6P+np6SouLu71/DQ3N7vqJamkpMSpP336tKLRqKsmGAwqEonc9JwPZHfiPKcSi8WUlpamrKysz2Td/dGdOtfJZFLz58/X97//fU2aNOnOLL6fubevSPjUotGoHnzwQVff4MGDdf/99ysajfa6jc/nu+E/cqFQyNnm6tWrmjdvnurr6zV69Og7svb+5E6d5z+2d+9ebdq0SQsXLvxM1v1FdunSJSUSCYVCIVf/zc5PNBq9af31Ty9zDnR34jz/se7ubi1ZskTz5s27p/+47Z061z/+8Y81ePBgfec73/nsF91PEZ6Q0tKlS5WWlnbTdvz48Tu2/2XLlulLX/qSvvnNb96xfXwR3O3z/Ent7e0qKytTdXW1Zs6c+bnsE/i0rl27prlz58rM9Ld/+7d3ezkDTmtrq/7mb/5GGzduVFpa2t1ezhfG4Lu9AHwx/dVf/ZW+9a1v3bTm4YcfVjgc1sWLF139H3/8sT744AOFw+GU24XDYfX09Kirq8t1V6Szs9PZ5je/+Y0OHz6sX/7yl5L+8AaTJI0cOVL//b//d/3gBz+4zSP7Yrnb5/m6o0ePqqioSAsXLtRf//Vf39ax9DcjR47UoEGDbnjLM9X5uS4cDt+0/vpnZ2ensrOzXTWPPfbYZ7j6/uNOnOfrrgen9957T7/5zW/u6btO0p051//6r/+qixcvun4DkEgk9Fd/9Vd67bXX9O677362B9Ff3O2HrtC/XX+Q+e2333b6fvWrX/XpQeZf/vKXTt/x48ddDzKfOnXKDh8+7LQ33njDJNnevXt7fWtkILtT59nMrL293R588EH7/ve/f+cO4AsqPz/f/vIv/9L5nkgkbNSoUTd9uPZrX/uaq6+goOCGB8ZXrlzpjMdiMR4Y/4zPs5lZT0+PlZeX26RJk+zixYt3ZuH90Gd9ri9duuT6b/Hhw4ctJyfHlixZYsePH79zB/IFR3jCp1ZaWmqPP/64tbS02P/9v//XHn30Udcr9OfOnbMJEyZYS0uL0/f888/b6NGj7Te/+Y29/fbbVlBQYAUFBb3uY/fu3ff023Zmd+Y8Hz582B544AH75je/aR0dHU67Vy5GjY2N5vf7bePGjXb06FFbuHChZWVlWTQaNTOz+fPn29KlS536t956ywYPHmwrV660Y8eOWXV1dcp/qiArK8u2bdtmhw4dsrKyMv6pgs/4PPf09NjXv/51e+ihh+ydd95x/exevXr1rhzjF8Wd+Jn+Y7xtR3jCZ+D999+3efPm2X333WeZmZn27LPP2uXLl53x06dPmyTbvXu303flyhX7i7/4CxsxYoQNHTrU/ut//a/W0dHR6z4IT3fmPFdXV5ukG9qYMWM+xyO7u1avXm2jR482n89n+fn5tm/fPmessLDQKioqXPWbN2+28ePHm8/ns0mTJtmOHTtc48lk0pYvX26hUMj8fr8VFRXZiRMnPo9D+UL7LM/z9Z/1VO2TP//3qs/6Z/qPEZ7M0sz+v4dJAAAAcEu8bQcAAOAB4QkAAMADwhMAAIAHhCcAAAAPCE8AAAAeEJ4AAAA8IDwBAAB4QHgCAADwgPAEAADgAeEJAADAA8ITAACAB4QnAAAAD/4fES6rOMOct/kAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot(d_time[10])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:35:25.122861Z",
     "end_time": "2023-05-18T12:35:25.251943Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x7feef26c8e80>]"
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "smalld_time = d_time[:15]\n",
    "plt.plot(d_time[int(1e6):int(1.1e6)])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:46:01.494137Z",
     "end_time": "2023-05-18T12:46:02.632876Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "outputs": [
    {
     "data": {
      "text/plain": "0.00200000000018008"
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_time[int(1e6)+7]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:46:59.353619Z",
     "end_time": "2023-05-18T12:46:59.376776Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "outputs": [
    {
     "data": {
      "text/plain": "1100000.0"
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1.1e6"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:45:45.752302Z",
     "end_time": "2023-05-18T12:45:45.756303Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x7feef2b32dc0>]"
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sin = np.array([np.sin(t) for t in np.linspace(0,40,num=100)])\n",
    "plt.plot(sin)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:35:49.549922Z",
     "end_time": "2023-05-18T12:35:49.690025Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100,)\n",
      "(15610999,)\n"
     ]
    }
   ],
   "source": [
    "print(sin.shape)\n",
    "print(d_time.shape)\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-18T12:36:22.148996Z",
     "end_time": "2023-05-18T12:36:22.161663Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "cut = raw.time_as_index([10.,2e10])\n",
    "cute = raw[:,cut[0]:cut[1]]\n",
    "len(cute[1])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-17T15:18:15.743459Z",
     "end_time": "2023-05-17T15:18:16.482119Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "print(raw.info['chs'])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-17T15:28:22.377724Z",
     "end_time": "2023-05-17T15:28:22.426250Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "type(raw.info)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-05-17T15:26:44.243008Z",
     "end_time": "2023-05-17T15:26:44.248009Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "raws = [import_ecg(f) for f in names]\n",
    "for raw in raws:\n",
    "    max =\n"
   ],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
